Regional and temporal variations in COVID-19 cases and deaths in Ethiopia: Lessons learned from the COVID-19 enhanced surveillance and response

Background The COVID-19 pandemic is one of the most devastating public health emergencies of international concern to have occurred in the past century. To ensure a safe, scalable, and sustainable response, it is imperative to understand the burden of disease, epidemiological trends, and responses to activities that have already been implemented. We aimed to analyze how COVID-19 tests, cases, and deaths varied by time and region in the general population and healthcare workers (HCWs) in Ethiopia. Methods COVID-19 data were captured between October 01, 2021, and September 30, 2022, in 64 systematically selected health facilities throughout Ethiopia. The number of health facilities included in the study was proportionally allocated to the regional states of Ethiopia. Data were captured by standardized tools and formats. Analysis of COVID-19 testing performed, cases detected, and deaths registered by region and time was carried out. Results We analyzed 215,024 individuals’ data that were captured through COVID-19 surveillance in Ethiopia. Of the 215,024 total tests, 18,964 COVID-19 cases (8.8%, 95% CI: 8.7%– 9.0%) were identified and 534 (2.8%, 95% CI: 2.6%– 3.1%) were deceased. The positivity rate ranged from 1% in the Afar region to 15% in the Sidama region. Eight (1.2%, 95% CI: 0.4%– 2.0%) HCWs died out of 664 infected HCWs, of which 81.5% were from Addis Ababa. Three waves of outbreaks were detected during the analysis period, with the highest positivity rate of 35% during the Omicron period and the highest rate of ICU beds and mechanical ventilators (38%) occupied by COVID-19 patients during the Delta period. Conclusions The temporal and regional variations in COVID-19 cases and deaths in Ethiopia underscore the need for concerted efforts to address the disparities in the COVID-19 surveillance and response system. These lessons should be critically considered during the integration of the COVID-19 surveillance system into the routine surveillance system.

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Competing Interests
On behalf of all authors, disclose any competing interests that could be perceived to bias this work.This statement will be typeset if the manuscript is accepted for publication.All aggregated COVID-19 surveillance and response data used in this study will be made available in the EPHI data repository after publication.Access to data will be provided following the investigators' approval of a proposal.Request for the data should be directed to the corresponding author.People requesting data will need to sign a data access agreement that will be forwarded upon request and the database will be transferred electronically.

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system.These lessons should be critically considered during the integration of the COVID-19 surveillance system into the routine surveillance system.Keywords: COVID-19, Surveillance, Ethiopia, Variation

Introduction
The COVID-19 pandemic has been one of the most devastating Public Health Emergencies of International Concern (PHEIC) of this century, with a high burden of cases and deaths globally [1].The COVID-19 pandemic has tested the resilience of the global public health system and threatened the existing fragile public health systems [2,3].To contain the spread of the disease, several global and local initiatives and preventive measures were implemented.Some of these measures were a consequence of the World Health Organization's (WHO) decision to declare COVID-19 as a PHEIC [4] and of the Ethiopian government to declare a State of Emergency, where travel restrictions, school closures, and a ban on public gatherings were implemented.
The WHO recommended COVID-19 surveillance as one of the critical measures necessary to end the pandemic and effectively inform public health responses to limit the spread of the disease and its impacts [5].It is critical for new cases and clusters of infections to be rapidly identified before widespread transmission occurs [6].Surveillance for COVID-19 is important to understand long--term epidemiological trends of morbidity and mortality, early warning of changes in epidemiological patterns, the burden of disease on healthcare capacity, circulation of known variants of concern (VOCs), and early detection of new variants of concern.Thus, it was critical to build a resilient public health surveillance system to allow early detection, prevention, and response of COVID-19 in an effective and timely manner [5][6][7].To this end, Ethiopia implemented several COVID-19 surveillance and response activities to reduce the spread of the pandemic which included active case detection, contact tracing, care and isolation, and quarantine [8][9][10].
To strengthen surveillance for COVID-19 and other reportable diseases, a Coronavirus Relief and Economic Security (CARES) Act was enacted by the U.S. government.The U.S. Centers for Disease Control and Prevention (CDC) funded the Ethiopian National Surveillance Project with CARES funding through a cooperative agreement.The project allowed implementation of different activities through partnership among the Ethiopian Public Health Institute (EPHI), Regional Health Bureaus (RHBs), The Ohio State University Global One Health initiative (GOHi), the ICAP at Columbia University and other partners.Through the project, key interventions to augment the existing COVID-19 surveillance and response system capacity were implemented at both national and regional levels in selected healthcare facilities throughout Ethiopia.Accordingly, COVID-19 surveillance and response data were actively captured from supported healthcare facilities and reported to the EPHI in a systematic and timely manner.As COVID-19 emergency phase ends, Ethiopia is working to integrate its surveillance into the routine public health surveillance system as per the WHO recommendations [11].Consequently, it is critical to adequately understand the burden of the disease, patterns of outbreaks, and response activities to be sustained and scaled up.This study report is uniquely comprehensive at the national scale.Only a few regional studies on the clinical and epidemiological profile of COVID-19 cases in Ethiopia have been published [10,[12][13][14].These studies reported a limited number of cases and lacked information related to the epidemiological and temporal link among the different waves of outbreaks.In addition, prior studies do not adequately correlate surveillance and response efforts carried out during the outbreaks, nor did the studies analyze the burden of the disease among HCWs.To ensure a safe, scalable, and sustainable transition of the surveillance system, it is imperative to understand trends and responses to COVID-19 from the analysis of nationally representative data captured through this collaborative project.Here we describe the burden of COVID-19 (morbidity and mortality), epidemiological trends, the burden on the healthcare capacity, and response to control spread during the project implementation period.

Study Setting, Design, and Selection of Healthcare Facilities
The public health surveillance system in Ethiopia follows the healthcare delivery systems structure with administrative hierarchies within the national health system including the primary healthcare level (health posts, health centers, districts, hospitals), secondary healthcare level (general hospitals), and tertiary healthcare level (specialized comprehensive hospitals).The woreda, zonal, regional, and federal (EPHI) health offices are responsible for coordinating the overall public health surveillance and response systems for each respective level [15].COVID-19 surveillance was structured in a similar manner, utilizing these healthcare levels [16].
The healthcare facilities (health centers and hospitals) were responsible for capturing COVID-19 cases and daily reporting to higher administrative levels.Our descriptive, cross-sectional study was conducted using the analysis of COVID-19 surveillance and response data captured from 64 of these selected healthcare facilities between October 01, 2021 and September 30, 2022.Among the selected healthcare facilities, 31 were primary level, 21 were secondary level, and 12 were tertiary level healthcare facilities.Selection of facilities was systematically based on reported patient load (high-load facilities were selected), availability of COVID-19 testing service, and access to electricity.The number of healthcare facilities included was proportionally allocated to the regional states of Ethiopia to ensure representation of all geographical areas of the country.
However, due to the conflict in Northern Ethiopia (Tigray region), we were unable to include that region in this study.The selected health facilities were supported by the CARES Act project through provision of designated public health surveillance officers responsible for carrying out COVID-19 surveillance activities to capture data and share reports to the next level in the health system.

Data Collection Tools and Procedures
To ensure the quality of surveillance data and minimize variability, standardized training on COVID-19 surveillance was provided to the public health surveillance officers, continuous mentorship and supportive supervision of officers at reporting facilities were provided regularly (every two months), and completeness and timeliness reports were generated at regional and central levels, with feedback continuously being provided to the reporting facilities.
Surveillance data were captured in healthcare facilities using standardized COVID-19 surveillance tools and case definitions (S1 Appendix) adapted from the national COVID-19 surveillance guideline and the WHO COVID-19 surveillance interim guideline [16,17].The deployed public health surveillance officers (Master of Public Health degree holders) were responsible for capturing COVID-19 surveillance data from clients, registering cases in the COVID-19 surveillance logbooks, and reporting to higher levels through the DHIS2 system or via e-mailing of Excel spreadsheets.The COVID-19 surveillance tools captured data on suspect case identification and testing status, number of confirmed cases, COVID-19 testing modality, number of admissions and deaths, contacts identified and tested, number of confirmed HCW cases and deaths, number of clusters/outbreaks investigated, and responses provided.Cluster investigation was conducted following WHO standard procedures (S1 Appendix) [18].

Data Management and Analysis
Public health surveillance data were retrieved from different sources (e.g., DHIS2 and Excel spreadsheets) and compiled into one master Excel sheet, cleaned, checked for completeness, and exported to SPSS version 25 software for analysis.Descriptive analysis (frequency and proportions) was carried out and presented in tables and figures while trends of COVID-19 tests, cases, and deaths were presented in line graphs.Calculations for all metrics can be found in Table 1.For analysis, all data were stratified by regional state.

Results
This study relied on surveillance data from 215,024 COVID-19 suspected cases, contacts, and travelers tested by either the Antigen Detection Rapid Diagnostic Test (Ag RDT) (88.9%) or Real-Time Polymerase Chain Reaction (RT-PCR) (11.1%) from 64 health facilities.The average completeness and timeliness of the data were 98.1% and 97.9%, respectively (Figure 1).

COVID-19 Testing and Case Detection
Out of the 215,024 COVID-19 suspected cases, contacts, and travelers tested, 88.9% were tested by Ag RDT and 11.1% were tested by RT-PCR.However, facilities in the Harari and Benishangul Gumuz regions used only Ag RDT (100%) as a testing modality.The majority of tests were performed at the secondary healthcare level (general hospitals).One-third (33%) of the testing and one-third (33%) of cases were from facilities in Addis Ababa (Figure 2).Among those tested, 18,964 were found to be positive for COVID-19, with a positivity rate of 8.8% (95% CI: 8.7% -9.0%).The positivity rate ranged from 1% in the Afar region to 15% in the Sidama region (Table 2).Three waves of outbreaks were detected during the analysis period.The first peak occurred during Epi-weeks 39 and 40 of 2021 (October 2021).The second peak occurred from Epi-week 50 of 2021 to Epi-week 2 of 2022 (Dec 12, 2021 -Jan 15, 2022) and sharply declined from Epi-week 2 to Epi-week 4 of 2022 (Jan 15 -31, 2022).During this second peak period, the positivity rate reached as high as 35%.The curve remained flat until Epi-week 20 of 2022 (May 13, 2022) after which it began to rise and a third wave was detected from Epi-week 24 to Epi-week 26 of 2022 (June 12 -July 02, 2022) after which the curve declined (Figure 3).
The second wave (December 2021) was attributed to the Omicron variant, which was characterized by a higher positivity rate, but lower severity.During this wave, more than one out of three individuals tested were found to be positive for COVID-19.Omicron cases were less symptomatic, resulted in fewer hospital admissions for those who were unvaccinated and for those who were already immunized after the booster dose and were associated with quicker recovery [19,20].The third wave (January 2022) was attributed to the Omicron subvariant, which had similar characteristics to the Omicron variant in terms of positivity and severity [19].
The overall positivity rate in our study was relatively lower than study reports from other countries.
However, there was regional variation in the positivity rate.For instance, consistent with other studies, [13,14] nearly one-third of the tested patients in Addis Ababa (the capital city) was found to be positive for COVID-19, while only 1% and 2% positivity were reported in the Afar and Somali regions, respectively.These findings could be due to facilities are close to the point of entry (PoE) in these two regions, where the majority of the tested clients are border-crossing clients.Moreover, the lower positivity rates in the regions might be due to the warm weather of the regions, as consistent findings were reported from a study in Pakistan [21].
The COVID-19 CFR among all confirmed cases is higher in our study than the national CFR (2.8 compared to 2.0%) for the same period.This variation could be explained by the type of surveillance we employed ─ health facility-based versus the national surveillance system, which includes facility-based, community-based, point-of-entry, and mortality surveillance types [16].It is likely symptomatic and possibly severe COVID-19 cases with comorbidities were captured by facility-based surveillance.
Similar to other countries, [22,23] a substantial number of HCWs were found to be infected and died of COVID-19 in Ethiopia.This has several implications for clinical and public health practices.As the ratio of HCWs to the population in Ethiopia is low, their infection and death substantially affected the capacity of the healthcare system to respond to the pandemic and other diseases.HCWs are part of the basic elements of health systems and their contribution is critical to achieving global health security and universal health coverage [24].Moreover, the infection and death of HCWs may indicate poor infection prevention and control (IPC) strategies and practices, including limited availability and appropriate use of personal protective equipment (PPE) [25][26][27][28].
Therefore, it is critical for the country to adapt and execute critical precautionary measures to reduce HCW infection and death and ensure a safe and sustainable COVID-19 surveillance system is implemented.
This study analyzed data captured from a well-monitored, collaborative COVID-19 surveillance project covering all regions of Ethiopia.The analysis included data captured over a full year period including regional variation in the number (proportion) of tests, cases, deaths, and HCWassociated infections and deaths to fully understand trends and justify identified variations.
However, this study has some limitations.Results were not able to capture more fine-scale variation because the study relied on aggregate surveillance data as opposed to individual, patientlevel data.COVID-19 surveillance data were not able to be captured in the Tigray region and some parts of the Amhara and Afar regions due to conflict which may limit the generalization of our findings to the country as a whole.Further, the surveillance system may not adequately capture COVID-19 cases with asymptomatic or mild clinical course at the community level.
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Table 4 : Healthcare workers' infection and death by region and facility type
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